network analysis
Graph-theoretical approach to studying brain connectivity patterns by representing brain regions as nodes and connections as edges in mathematical networks.
Full Definition
Network analysis applies graph theory principles to study brain connectivity by representing neural systems as mathematical networks composed of nodes (brain regions) and edges (connections between regions). This approach characterizes network properties including clustering coefficient, path length, small-worldness, modularity, and hub identification. Network analysis can be applied to both structural connectivity (derived from diffusion imaging) and functional connectivity (from correlation analyses) data. The method has revealed important organizational principles of brain networks, including the presence of highly connected hub regions, modular organization, and small-world topology that balances local clustering with global integration. Network measures have proven sensitive to development, aging, and disease processes.
Usage
Usage note: Specify whether analyzing structural or functional networks; define node and edge definitions clearly.
In Context
- "Network analysis revealed reduced small-world properties in patients with schizophrenia." — Clinical connectivity study
- "Graph-theoretical metrics were computed to characterize network topology changes with aging." — Developmental neuroimaging paper